During the past 18 months, I served as an academic officer ("curriculum coordinator") in what was then known as the UC Berkeley Division of Data Sciences, and which will be one of the elements of the new Division of Data Science and Information. I left the Division in early December to switch to a research role across the bay at UCSF.
My involvement with what became the Division stretches back to Fall 2015, when Cathryn Carson brought me on to teach one of the 6 inaugural Data Science Connector courses that term. Connector courses are usually small seminar-style, half-time offerings (2 units rather than 4) that aimed to connect concepts in the foundational course at Berkeley, Data 8, to topics in academic fields. I taught a connector entitled "Health, Human Behavior, and Data" during that first term of Data Science at Berkeley, and again in Spring 2016. During the academic year 2016-2017, I taught statistics and econometrics at Mills College in Oakland.
Looking back on my involvement with Data Science these past several years and over the arc of my own education and career, I feel a sense of great pride and awe at what the group at Berkeley has accomplished. As a sophomore in Fall 1993, I studied computer science in the introductory course COS 126 taught by Robert Sedgewick at Princeton 25 years ago, during the same term I studied econometrics led that fall term by Henry Farber. I had my hands full. There were many Sundays when I didn't get to sleep until very late, working on problem sets for both classes, sometimes via a dialup modem on a Mac SE from my dorm room.
In 1993, econometrics was its own thing, and computer science seemed like it was all about loops and "pointers" whatever in the world those were. But Stata lived on three UNIX mainframes that all of us had access to, and there was some synergy to be had in studying C++ and applied econometrics in Stata at the same time. I definitely learned plenty of UNIX along the way.
I wish that modern Data Science had been around back then, and it thrills me to see it here now, at last. No joke, I earned a C in COS 126 that term, although I got an A in econometrics. I suppose a C+ in COS 126 would have been somewhat more appropriate! Back then, it was tough to straddle both worlds without destroying one's GPA. Now, it is far more seamless.
Students in Berkeley Data Science certainly include many folks who are Comp Sci whiz kids. But they also include many who were a lot more like I was in 1993, along with folks even further toward the social side of social science, and people in the humanities. Berkeley has figured out a great way of planting poles so widely that the tent is truly big. It has been a great pleasure watching and helping it unfold.
